Demand-Side Management of Solar Microgrid Operation: Effect of Time-of-Use Pricing and Incentives

Abstract

Over 17% of the world’s population lack access to electricity, the majority being in rural areas of sub-Saharan Africa and South Asia. Microgrid technologies are a promising solution towards rural and remote area electrification; however, ever-increasing electricity demand remains a big challenge leading to pronounced power outages. Demand-side management is an indispensable tool towards addressing the challenges. This paper employs a mathematical model based on incentives and time-of-use rates to simulate daily power usage pattern of residential customers using data collected from an isolated village Ngurdoto solar microgrid, Arusha, Tanzania. Customer responsiveness on the increase in price was evaluated based on the concept of price elasticity of demand. Using two demand response strategies, namely, load shifting (LS) and scheduled load reduction (SLR), the results reveal that LS can achieve up to 4.87% energy-saving, 19.23% cost-saving, and about 31% and 19% peak reduction and power factor improvement, respectively. SLR method resulted in about 19% energy-saving, 49% cost-saving, and 24% power factor improvement. Thus, the results presented in this study may lead to a more efficient and stable system than the current state in developing countries’ utility.

Various demand side management techniques and its role in smart grid–the state of art

“…The goal is to alter the load profile during peak hours using different attractive schemes by meeting the overall requirements. DR is the method of changing the load profiles of consumers with the help of additional incentives or cost-saving systems [9]. The basic idea of DR is a mutual understanding among service providers and consumers [10].…”

Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping

“…Poor access to electricity in rural areas has been linked to community development gaps, leading to rural to urban migration and putting further stress on already strained urban infrastructure systems [7][8][9]. However, in Sub-Saharan African countries, only about two-fifths of the population has access to electricity, the lowest proportion in the world [3,10]. In East Africa, the situation is still critical, since about 80% of the population has no or unreliable access to electricity, the majority being people in rural areas [11,12].…”

“…Microgrids have several advantages, such as their ability to create a decentralized system of aggregated loads, and even in the scenario of interconnection, the option of operating in an isolated mode [15]. However, microgrids face several setbacks regarding stability and reliability due to their intermittent nature, the non-uniform distribution of renewable energy resources and the stochastic behavior of energy needed to power loads [10]. During periods of low renewable energy production, where the energy generated is insufficient to cater to the increased demand, energy storage and/or load shedding are adopted to address energy deficits [16,17].…”

“…During periods of low renewable energy production, where the energy generated is insufficient to cater to the increased demand, energy storage and/or load shedding are adopted to address energy deficits [16,17]. Load shedding is when utilities intervene on the supply side to reduce power consumption, whereby customers are disconnected for a particular time [10,18]. Customers usually dislike this experience, as it is a source of several losses and discomforts [18].…”

“…Load shifting gives consumers options to shift their usage pattern to off-peak hours based on cheap tariffs. It is the combination of load clipping and valley filling [10,12]. Flexible load shaping is when consumers are flexible enough to shift their loads to different low usage slots.…”